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Biography
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Zhenghao Guo is an Assistant Professor in Biomedical Engineering. He earned his Ph.D. from the Department of Engineering, King's College London (2023 QS Global Ranking 37), under supervision of Prof. Zoran Cvetkovic (IEEE Senior Member) and Prof. Osvaldo Simeone (IEEE Fellow). He holds a Master's degree from the College of Information Science and Technology, Beijing Normal University (985/211 Project), under supervision of Prof. Bin Hu (IEEE Fellow) and Prof. Xia Wu (IEEE Senior Member). Dr. Guo completed his Bachelor's degree at College of Computer Science, Sichuan University (985/211 Project).
Dr. Guo's primary research areas include signal processing, information theory, machine learning, system identification, and their applications in biomedical engineering. As the lead author, he has contributed to multiple publications in prestigious international journals, such as IEEE Transactions on Biomedical Engineering and the Journal of Neural Engineering. Dr. Guo has also presented his research at several high-profile international academic conferences, including IEEE ICASSP and IEEE EMBC.
People with an interest in the field of biomedical signal processing are warmly invited to get in touch: zhenghaoguo@dlut.edu.cn.
Education
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Time Degree | Major University | College Supervisor 10/2018 - 06/2023 Doctor of Philosophy
Electronic EngineeringDepartment of Engineering
King's College LondonProf. Zoran Cvetkovic
Prof. Osvaldo Simeone09/2015 - 06/2018 Master of Engineering
Computer Application TechnologyCollege of Information Science and Technology
Beijing Normal UniversityProf. Bin Hu
Prof. Xia Wu09/2011 - 06/2015 Bachelor of Engineering
Computer Science and TechnologyCollege of Computer Science
Sichuan University
Employment
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Time Position Employer 10/2023 - Now Assistant Professor School of Biomedical Engineering
Dalian University of Technology
Research Interest...
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Signal Processing (Time-frequency Analysis, Wavelets)
Information Theory (Entropy, Mutual Information, Transfer Entropy)
Machine Learning (Dictionary Learning, Sparse Representation, Optimization, Feature Selection, Classification, Clustering)
Linear System Identification (Errors-in-variables Systems)
Biomedical Signal Processing
Selected Publicat...
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[1] Guo, Z.*, Xu, Y., Rosenzweig, J., McClelland, V.M., Rosenzweig, I. and Cvetkovic, Z., 2024. Subband independent component analysis for coherence enhancement. IEEE Transactions on Biomedical Engineering. (JCR:Q1, IF: 4.756)
[2] Guo, Z., Lin, J.P., Simeone, O., Mills, K.R., Cvetkovic, Z. and McClelland, V.M.*, 2024. Cross-frequency cortex-muscle interactions are abnormal in young people with dystonia. Brain Communications. (JCR:Q1, IF: 4.800)
[3] Guo, Z., Lin, J.P., Simeone, O., Mills, K.R., Cvetkovic, Z. and McClelland, V.M.*, 2024. Cross-frequency cortex-muscle interactions are abnormal in young people with dystonia. Developmental Medicine & Child Neurology. (Abstract, JCR:Q1, IF: 3.800)
[4] Guo, Z.*, McClelland, V.M., Simeone, O., Mills, K.R. and Cvetkovic, Z., 2021. Multiscale wavelet transfer entropy with application to corticomuscular coupling analysis. IEEE Transactions on Biomedical Engineering. (JCR:Q1, IF: 4.756)
[5] Guo, Z., Wu, X.*, Liu, J., Yao, L. and Hu, B., 2018. Altered electroencephalography functional connectivity in depression during the emotional face-word Stroop task. Journal of Neural Engineering. (JCR:Q1, IF: 5.043)
[6] Guo, Z.*, McClelland, V.M., Dai, W., Cong, F. and Cvetkovic, Z., 2024, July. Weighted errors-in-variables modelling for detection of cortico-muscular couplings. In 2024 46th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE.
[7] Guo, Z.*, McClelland, V.M., Dai, W. and Cvetkovic, Z., 2023, June. Structured errors-in-variables modelling for cortico-muscular coherence enhancement. In ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE.
[8] Guo, Z.*, McClelland, V.M. and Cvetkovic, Z., 2021, November. Unravelling causal relationships between cortex and muscle with errors-in-variables models. In 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE.
[9] Guo, Z., Wu, X. and Hu, B.*, 2018, April. Abnormally decreased functional connectivity of affective interference in depression based on electroencephalography. In 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI). IEEE. (Abstract)
[10] Guo, Z., Long, H., Yao, L., Wu, X.* and Cai, H., 2017, November. Abnormal EEG-based functional connectivity under a face-word Stroop task in depression. In 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE.
Group Members
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